Skill audit report
Query Fabric lakehouse and warehouse data using DuckDB, either locally or inside a Fabric notebook. Automatically invoke when the user mentions "DuckDB", "query Delta tables locally", or asks to "attach DuckDB to a lakehouse", "query OneLake data", "explore lakehouse data", "data freshness check", "validate data quality", "use DuckDB in Fabric".
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO76
887 GitHub stars
Stars/forks activity
INFO71
887 stars, 131 forks; issue activity unavailable in current metadata
Recent maintenance
PASS88
1mo since push
License clarity
PASS86
GPL-3.0
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
FAIL36
command execution surface, credential or environment access
Install availability
PASS92
npx skills add data-goblin/power-bi-agentic-development --skill using-duckdb
Install command safety
PASS92
standard package or runtime install path
Permission surface
FAIL24
secrets or environment access, shell or command execution
Repository evidence
PASS86
https://github.com/data-goblin/power-bi-agentic-development/tree/main/plugins/etl/skills/using-duckdb
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add data-goblin/power-bi-agentic-development --skill using-duckdb
Repository
88
https://github.com/data-goblin/power-bi-agentic-development/tree/main/plugins/etl/skills/using-duckdb
License
86
GPL-3.0
Maintenance
88
1mo since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
Usable description available
Dependency risk
36
command execution surface, credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
24
secrets or environment access, shell or command execution
Stars/forks activity
71
887 stars, 131 forks; issue activity unavailable in current metadata
Adoption
88
887 GitHub stars
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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